How AI Uses Noise to Protect Your Data (Differential Privacy)
AI Summary
This video discusses the challenges of ensuring individual privacy when handling large datasets. The speaker emphasizes the need for proper data lineage and tracking of hyperparameters to mitigate privacy risks. It highlights the importance of synthetic data in maintaining control over exposure risks. The concept of differential privacy is explained, particularly through the use of aggregated queries and the addition of noise to data to protect individuals while still allowing for meaningful data analysis.